Hyperspectral imaging for early detection of Alzheimer&#39;s disease

ABSTRACT

Described herein is the use of a visible near infrared (VNIR) hyperspectral imaging system as a non-invasive diagnostic tool for early detection of Alzheimer&#39;s disease (AD). Also described herein is the use of a VNIR hyperspectral imaging system in high throughput screening of potential therapeutics against AD.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This patent application is a continuation of U.S. application Ser. No.16/160,208, filed on Oct. 15, 2018, which is a continuation of U.S.application Ser. No. 15/449,585, filed on Mar. 3, 2017, now U.S. Pat.No. 10,098,540, which is a continuation of U.S. application Ser. No.14/363,953, filed on Jun. 9, 2014, now U.S. Pat. No. 9,585,558, which isa 35 U.S.C. § 371 application of International Application No.PCT/US2012/068793, filed on Dec. 10, 2012, which claims the benefit ofpriority of U.S. application Ser. No. 61/568,983, filed Dec. 9, 2011,which applications are herein incorporated by reference.

BACKGROUND

There are currently no methods for detecting Alzheimer's Disease (AD)prior to β-amyloid plaque formation. Unfortunately, current methods candetect AD only after a patient starts showing cognitive symptoms. Assuch, methods to detect AD at an early stage, e.g., before β-amyloidplaque formation, are needed.

Summary of Certain Embodiments of the Invention

Accordingly, certain embodiments of the present invention provide amethod for determining whether a subject has Alzheimer's Disease (AD),or is predisposed for developing AD, comprising obtaining ahyperspectral image (HSI) from the eye (e.g., the retina) of the subjectand determining whether the HSI comprises spectral differences that areindicative of AD, wherein the presence of said spectral differences thatare indicative of AD indicates the subject has, or is predisposed (e.g.,at an elevated risk as compared to the general population) fordeveloping, AD. Whether a subject is at an elevated risk as compared tothe general population for developing AD is determined by the presenceof risk factors detected by HSI, e.g., in the absence of blatantmorphological changes in brain or retina tissue of the patient, such asβ-amyloid plaque formation.

In certain embodiments, the HSI is a visible near infrared (VNIR) HSI.

In certain embodiments, the HSI is obtained using wavelengths up toabout 2500 nm. In certain embodiments, the HSI is obtained usingwavelengths from about 400 nm to about 2500 nm, e.g., about 400 nm toabout 1400 nm, e.g., about 400 nm to about 1000 nm.

In certain embodiments, the HSI is compared to at least a first previousHSI obtained from the subject at an earlier point in time (e.g., from atleast one previous annual check-up), wherein significant spectraldifferences between the HSI images indicates the subject has AD.

In certain embodiments, the HSI from the subject is compared to acontrol reference HSI and to an AD reference HSI to determine whetherthe image comprises spectral differences that are indicative of AD.

In certain embodiments, the subject (e.g., a human male or female) isfrom about 30-80 years old, e.g., 30-50 years old. In certainembodiments, the subject is about 25-30 years old, about 30-35 yearsold, about 35-40 years old, about 40-45 years old, about 45-50 yearsold, about 50-55 years old, or about 55-60 years old.

In certain embodiments, the HSI(s) is/are obtained via a retinaexamination through whole eye of a patient.

In certain embodiments, the subject is a male.

In certain embodiments, the subject is a female.

Certain embodiments of the present invention provide a method fordetermining whether a treatment is effective in treating Alzheimer'sDisease (AD), comprising determining whether the treatment causes adecrease in spectral differences that are indicative of Alzheimer'sDisease (AD) from a hyperspectral image (HSI) from a retina examination,e.g., through the whole eye of a patient. In certain embodiments, themethod is an in vitro method.

In certain embodiments, the methods described herein are in vivomethods.

In certain embodiments, the methods described herein are in vitromethods.

In certain embodiments, the sample is retinal tissue.

Certain embodiments of the present invention provide a method for usinghyperspectral imaging for determining whether a test compound affectsβ-amyloid aggregation, comprising contacting a cell that comprisesβ-amyloid with the test compound, obtaining a hyperspectral image (HSI)of the cell, and determining whether the test compound affects β-amyloidaggregation.

In certain embodiments, a decrease in β-amyloid aggregation indicatesthat the test compound is an inhibitor of β-amyloid aggregation.

In certain embodiments, the β-amyloid is Aβ₁₋₄₂.

In certain embodiments, the method is an in vitro method.

In certain embodiments, the method is an in vivo method.

In certain embodiments, the cell is comprised in a population of cellsin a retina.

In certain embodiments, the HSI is a visible near infrared (VNIR) HSI.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 depicts a VNIR hyperspectral imaging system integrated into amicroscope assembly, thereby enabling pixel-level spectralquantification of the sample being imaged. This image shows the assemblywith a Cytoviva microscope.

FIG. 2 depicts the concentration-dependent uptake of FITC-labeledβ-amyloid peptide. As the concentration of β-amyloid peptide in theextracellular medium was increased, there was a dose-dependent increasein the uptake of β-amyloid peptide inside SH-SY-5Y cells. This isvisible as aggregates inside the cells.

FIG. 3 depicts a typical hyperspectral image from cells. After obtainingthe images, several areas in the cytoplasm of cells were selected. Theseare the areas from which spectra were collected are the ROI (Regions OfInterest), displayed as solid black regions.

FIG. 4 depicts a graph of the cytoplasm of SH SY5Y cells. Spectralinformation in the range of 400-1000 nm was extracted from the selectedROIs. This data was then normalized and the means with standarddeviation calculated. This figure shows typical data from the cytoplasmof β-amyloid peptide treated and non-treated cells, with focusing on theregions (480-500 nm) and (880-900 nm) where the maximum statisticallysignificant differences were observed.

FIG. 5 depicts the time-dependence of cytoplasmic differences betweenβ-amyloid-treated and untreated cells. These data suggest that thespectral changes observed are also time-dependent. The maximal spectralchange after β-amyloid peptide treatment was observed after 48 h.However, the spectral data can be analyzed as early as 4 hours, makingit attractive from the point of view of high throughput screening.

FIG. 6 depicts hyperspectral imaging of human brain tissue samples.Slides containing frozen brain tissue samples from a normal adult human(82 years old) and from an 83 year old patient with AD were obtained.The temporal lobe of the brain was selected for this study due tomaximal damage observed in this region due to AD. Spectral signatureswere obtained from the cytoplasmic and nuclear regions of normal and ADbrain tissues. This demonstrates the applicability of HSI scanningtechniques in human tissue samples.

FIG. 7 depicts hyperspectral imaging of human brain tissue samples. Thisfigure shows the spectral changes observed in the brain samples from anormal individual and AD patient. Statistically significant changes wereobserved in the ranges of (480-500 nm) and (880-1000 nm).

FIG. 8 depicts various parts of an eyeball and an isolated whole mountretina sample.

FIG. 9 depicts retina scans of mice at the age of 2 months. Retinatissue was isolated from wild type and transgenic Alzheimer's mice atthe age of 2 months. Upon visual inspection, there were no significantdifferences in the morphology of retina tissue samples obtained fromwild type and Alzheimer's mice. The spectral scan showed a trend towarddecreased absorbance by Alzheimer's retina as compared to the wild typeretina.

FIG. 10 depicts retina scans of mice at the age of 4 months. Retinatissue was isolated from wild type and transgenic Alzheimer's mice atthe age of 4 months. Upon visual inspection, there were no significantdifferences in the morphology of retina tissue samples obtained fromwild type and Alzheimer's mice. The spectral scans of retinas andaqueous eye fluid did not show any significant differences between wildtype and Alzheimer's mice.

FIG. 11 depicts hyperspectral imaging of mouse retina at 6 months. Uponvisual inspection, there were no significant differences in themorphology of retina tissue samples obtained from wild type andAlzheimer's mice at 6 months. However, hyperspectral scans showedsignificant spectral differences between the wild type (upper 3 traces)and Alzheimer's (lower 2 traces) mice retinae. (At earlier time points(2 and 4 months), there did exist a trend toward a slight difference,but the spectral differences did not reach statistical insignificance.)

FIG. 12 depicts immunohistochemical staining of mouse brain at 6 monthswith β-amyloid antibody. This figure shows the staining of mouse brainwith β-amyloid antibody at the age of 6 months. The staining in theAlzheimer's brain is not very prominent, however, the spectral changesobserved (FIG. 11 ) in the retina are statistically significant. Thisshows the early detection capability of HSI.

FIG. 13 depicts immunohistochemistry of mouse brain at 7 and 8 months.The number and size of β-amyloid plaques has increased tremendously inthe mouse brain at 8 months. The spectral differences in the mouseretina are also showing corresponding increase in the differencesbetween wild type and Alzheimer's mice and are statisticallysignificant.

FIG. 14 depicts aspects of a spectral angle mapping (SAM) classificationalgorithm, which was selected due to its better performance than otherclassification algorithms for detection of β-amyloid aggregates inunknown samples. (see also Siddiqi et al., Cancer, 114(1), 13-21(2008)).

DETAILED DESCRIPTION

Described herein is the use of a visible near infrared (VNIR)hyperspectral imaging system as a non-invasive diagnostic tool for earlydetection of Alzheimer's disease (AD). Also described herein is the useof a VNIR hyperspectral imaging system in high throughput screening ofpotential therapeutics against AD. In certain aspects, a key principleof this invention is the use of hyperspectral imaging (HSI) as atechnique that integrates conventional imaging and spectrophotometry andenables pixel level spectral quantification of the sample being imaged.As an example, the Cytovia-HSI system used captures the VNIR (400-1000nm) spectrum within each pixel of the scanned field of view withsuperior signal to noise ratio. By evaluating an expanded spectrum oftransmitted light well beyond the visible spectrum, additionalinformation is gained to further characterize the cellular changescaused by β-amyloid aggregation and AD progression.

The utility of HSI spectral analysis in the identification ofintracellular amyloid pathology in a variety of test systems was alsoevaluated. To this end, as described herein, it has been discovered thatHSI yields unique and reproducible spectral signatures of amyloidpathology. In every single system tested, including in-vitro cellculture, excised brain tissue and retinal tissue, amyloidogenesis asquantified by HSI correlated well with traditional markers, such astissue damage and cognitive decline. Such signatures can be extractedfrom neuronal tissue as well as from retinae. The signatures observed inthis study can be obtained well before amyloid-induced morphological andcognitive damage indicators appear. The retinal source of diagnostic HSIdata will be very useful for early diagnosis of AD.

As described herein, a HSI system has been developed that can detectcytoplasmic changes before the formation of β-amyloid plaques. Use ofseveral known inhibitors of β-amyloid aggregation can reverse suchcytoplasmic changes, demonstrating the usefulness as a high throughputscreening method. Furthermore, when applied to the brain from an ADpatient, a HSI system detects significant spectral changes thatdifferentiate it from a normal human brain. The advantage of this methodover currently known systems is that this method is fast, non-invasive,does not require administration of an external agent and the wavelengthregion employed is harmless to human tissues. Furthermore, apart fromactual brain detection of AD, this technique has been successfullyapplied to detect the initiation of the disease in the eye (e.g.,retinal tissue) well before the development of signs in the brain of atransgenic animal model of AD. This will allow the lead time fortreatment of this disease and even effective prophylaxis, which iscurrently lacking in available detection methods. Certain aspects of theinvention are described in relationship to obtaining HSI of the retina.In certain embodiments, other samples such as blood, plasma, urine,spinal fluid or eye fluids besides retinal tissue may be used in themethods described herein.

Certain embodiments of the invention can be used to detect disordersresulting from amyloidopathy and/or amyloidosis, which are pathologiesresulting from abnormal protein folding. The final abnormal, andtypically toxic, form of the protein is a beta-pleated sheet structure.The primary sequence of the amyloid may vary from disorder to disorderand is not restricted to Aβ₁₋₄₂ (Kyle, British Journal of Haematology(2001), 144(3), 529-538) Examples of such amyloidosis are Alzheimer'sdisease, cerebral amyloid angiopathy, familial amyloid polyneuropathy,Parkinsons' disease, Huntington's disease and prolactinoma. (see, e.g.,Irvine et al., Molecular medicine (Cambridge, Mass.) 14 (7-8): 451-64)Amyloidoses may also include certain infectious diseases such astransmissible spongiform encephalopathies. (e.g., Bovine spongiformencephalopathy or Mad Cow Disease; Nature Structural Biology 8, 281(2001))

It is noted that wavelengths herein are generally described using thenanometer (nm) description of wavelength. As the art worker appreciates,it is possible to convert these units into another measuring form todescribe the wavelengths as an equivalent (e.g., as the wavenumber).

Accordingly, this technology is useful for early detection ofAlzheimer's disease in humans via retinal scan as well as the evaluationof the treatment AD patients are exposed to. This method can serve as atool for high throughput screening of new therapeutics against AD.

While existing technologies provide the detection of AD at very laterstages of the disease and thus resulting in the failure of availabletreatment options, the present invention provides very early detectionof the disease. Furthermore this method is non-invasive and does notrequire administration of external dyes/reagents for detection ofβ-amyloid plaques.

It has been demonstrated herein that the HSI scanning technique can beemployed to screen therapeutics against AD in an in vitro model system.The changes induced by AD in the brain of an AD patient overcorresponding normal individual have been successfully detected andconfirmed. Furthermore, the HSI scan for early detection of AD using aretinal scan of a transgenic animal model of AD even before anyobservable changes occur in the brains and retinal tissue of theseanimals has been successfully employed. Assessment of treatment successof a preclinical drug candidate in a transgenic animal model of AD viaretinal HSI spectral analysis and positive correlation of the HSIspectral results with behavioral and biochemical findings has also beendemonstrated.

There is major commercial interest in the development of detectionsystems for neurodegenerative diseases. For AD, there are no availablecommercial methods that can detect the disease before the onset of anysymptoms or before brain-damage. This imaging system is a “first” inthis area, in that it provides indications of Alzheimer's disease beforeonset of brain damage. Furthermore, it is extremely attractive towardcommercial development since it does not entail administration of axenobiotic into the patient. Toxicological testing is not needed becausethere is no “substance contact” of the imaging system with the patient.The financial barrier here is much, much less than any comparabledetection system. Further, there is a need to implement high-throughputscreens for potential therapeutics for Alzheimer's disease, but theseefforts are hindered by the lack of early-stage detection. Providedherein is a screening system for testing of drugs for early-onsettreatment of Alzheimer's disease. Effective, specific “prophylaxis” ofAlzheimer's disease has until now been impossible because the earlystage of Alzheimer's, when there is no brain damage, has not beendetectable with currently available systems. The methods describedherein make possible for the first time the design of prophylactics ofAlzheimer's disease by providing spectral signature detection of earlypathology in the brain and allows for the evaluation of theeffectiveness of a treatment.

Evidence suggests that brain damage in AD starts prior to β-amyloidplaque formation. Detection of β-amyloid aggregation at the solublestage will be helpful for successful treatment. As described herein, ithas been demonstrated in in vitro and in vivo model systems that it ispossible to detect AD at a very initial stage when there is nodetectable damage to the brain. From the drug discovery point of view,currently known screening/testing methods for AD therapeutics rely ondyes (e.g., curcumin, thioflavin-T) for detection of 3-amyloidaggregation or employ GFP/FITC tagged β-amyloid peptide in cell basedassays. The methods described herein overcome these drawbacks and doesnot require the addition of an extraneous reagent for inhibitorscreening.

The results from HSI based evaluation of the drug treatment can becorrelated with other testing methods such as cognition tests,biochemical tests such as degree of oxidative stress, and β-amyloidplaque load in mouse brain. In addition, a ‘positive control’ for ADtreatment can be included based on literature reports, and the resultsof the positive control can be validated in above said systems. Theconsensus between the results from HSI analysis and other testingmethods will help validate the utility of HSI scanning for determiningthe degree of success of an AD treatment.

Certain embodiments provide a method for determining whether a subjecthas Alzheimer's Disease (AD) or is predisposed for developing AD,comprising obtaining a hyperspectral image (HSI) of the retina of thesubject over a range of wavelengths to obtain a HSI spectrum anddetermining whether the spectrum is indicative of the formation ofsoluble β-amyloid aggregates, wherein the presence of said solubleβ-amyloid aggregates indicates the subject has AD or is predisposed fordeveloping AD.

In certain embodiments, the wavelengths used to obtain the HSI spectrumare in the visible near infrared (VNIR) range.

In certain embodiments, the HSI spectrum is compared to at least a firstprevious HSI spectrum obtained from the subject at an earlier point intime, wherein significant spectral difference between the HSI spectraindicates the subject has AD or is predisposed for developing AD.

In certain embodiments, the HSI from the subject is compared to acontrol reference HSI spectrum and to an AD reference HSI spectrum todetermine whether the image comprises spectral differences that areindicative of AD.

In certain embodiments, the subject is from about 30 to 80 years old(e.g., 30-50 years old).

In certain embodiments, the subject is a male.

In certain embodiments, the subject is a female.

In certain embodiments, the subject is a human.

In certain embodiments, the HSI spectrum is obtained via a retinaexamination through the whole eye of a patient.

Certain embodiments provide a method for determining whether a treatmentis effective in treating or preventing Alzheimer's Disease (AD) orpreventing the progress of AD, comprising obtaining a hyperspectralimage over range of wavelengths from a retina examination of a subjectand determining whether the treatment causes a decrease in formation ofsoluble β-amyloid aggregates that are indicative of Alzheimer's Disease(AD), wherein a decrease in formation of soluble β-amyloid aggregates isindicative of an effective treatment.

In certain embodiments, the retina examination is a retina examinationthrough the whole eye of a patient.

In certain embodiments, the sample is retinal tissue.

In certain embodiments, the method is an in vitro method.

In certain embodiments, the HSI is a visible near infrared (VNIR) HSI.

Certain embodiments provide a method for using hyperspectral imaging fordetermining whether a test compound affects β-amyloid aggregation,comprising contacting a cell that comprises β-amyloid with the testcompound, obtaining a hyperspectral image (HSI) of the cell over a rangeof wavelengths to obtain a HSI spectrum, and determining whether HSIspectrum indicates that the test compound affects β-amyloid aggregation.

In certain embodiments, a decrease in β-amyloid aggregation indicatesthat the test compound is an inhibitor of β-amyloid aggregation.

In certain embodiments, the β-amyloid is Aβ₁₋₄₂.

In certain embodiments, the method is an in vitro method.

In certain embodiments, the method is an in vivo method.

In certain embodiments, the cell is comprised in a population of cellsin a retina.

In certain embodiments, the HSI is a visible near infrared (VNIR) HSI.

Certain embodiments provide a method of treatment comprisingadministering a therapeutic indicated for treatment or prevention ofAlzheimer's Disease to a patient from whom a HSI spectrum has beenobtained from the patient's retina and wherein the HSI spectrumindicates the patient is presenting with Alzheimer's Disease or ispredisposed to developing Alzheimer's Disease.

Certain embodiments provide a method for determining whether a subjecthas a disorder associated with amyloidopathy and/or amyloidosis or ispredisposed for developing a disorder associated with amyloidopathyand/or amyloidosis, comprising obtaining a hyperspectral image (HSI) ofthe retina of the subject over a range of wavelengths to obtain a HSIspectrum and determining whether the spectrum is indicative of theformation of soluble amyloid aggregates, wherein the presence of saidsoluble amyloid aggregates indicates the subject has a disorderassociated with amyloidopathy and/or amyloidosis or is predisposed fordeveloping a disorder associated with amyloidopathy and/or amyloidosis.

Certain embodiments provide a method for determining whether a treatmentis effective in treating or preventing a disorder associated withamyloidopathy and/or amyloidosis or preventing the progress of adisorder associated with amyloidopathy and/or amyloidosis, comprisingobtaining a hyperspectral image over range of wavelengths from a retinaexamination of a subject and determining whether the treatment causes adecrease in formation of soluble amyloid aggregates that are indicativeof a disorder associated with amyloidopathy and/or amyloidosis, whereina decrease in formation of soluble β-amyloid aggregates is indicative ofan effective treatment.

Certain embodiments provide a method of treatment comprisingadministering a therapeutic indicated for treatment or prevention of adisorder associated with amyloidopathy and/or amyloidosis to a patientfrom whom a HSI spectrum has been obtained from the patient's retina andwherein the HSI spectrum indicates the patient is presenting with adisorder associated with amyloidopathy and/or amyloidosis or ispredisposed to developing a disorder associated with amyloidopathyand/or amyloidosis.

In certain embodiments, the disorder associated with amyloidopathyand/or amyloidosis is Alzheimer's disease, cerebral amyloid angiopathy,familial amyloid polyneuropathy, Parkinsons' disease, Huntington'sdisease, prolactinoma or a transmissible spongiform encephalopathy.

In certain embodiments, the disorder associated with amyloidopathyand/or amyloidosis is bovine spongiform encephalopathy or mad cowdisease.

Certain embodiments of the invention will now be illustrated by thefollowing non-limiting Examples.

Example 1 Spectral Scans

CytoViva Hyperspectral Imaging System

After each treatment, slides were examined utilizing a CytoVivamicroscope and hyperspectral imaging system (CytoViva-HyperspectralImaging System (HSI), Auburn, AL) mounted on an Olympus BX-41 opticalmicroscope. This system employs a darkfield-based illuminator thatfocuses a highly collimated light at oblique angles on the sample toobtain images with improved contrast and signal-to-noise ratio. Aconcentric imaging spectrophotometer containing aberration-correctedconvex holographic diffraction gratings was used with 1.29 nm spectralresolution (12.5 μm slit). The utilization of this concept obviated thenecessity of extraneous agents (e.g., staining or contrast agents), asthe core imaging technique relies on light scattering/transmittance andresolution of scattered/transmitted light in the visible and near-IRwavelengths. Light scattering is a property unique to every type ofinsoluble particulate matter, ergo, spectral information relayed by thistechnique correlates directly to the location and type (or size) ofparticulate matter in question. In this experiment, the ENvironment forVisualization (ENVI ver. 4.4) software was employed to control theresolution of scattered light and aggregation of 3-amyloid peptide wasthe subject of interest.

The images were captured at 40× magnification using ENVI software, whichis followed by extraction of spectral curves as described in the nextsection. The camera captured spectral responses from 400-1000 nm with amaximum readout time of 12 frames per second. To aid in theidentification of Aβ₁₋₄₂ aggregates in unknown samples, a spectrallibrary of Aβ₁₋₄₂ aggregates was created by scanning a stock solution ofAβ₁₋₄₂ peptide which was allowed to oligomerize in vitro. Afterestablishment of this reference library, the spectral angle mappingalgorithm was employed for comparison of the distinct spectral featuresof the library with the spectral scan of the unknown sample (describedin Spectral Angle Mapping Classification Algorithm). (seewww.cytoviva.com/product_hyperspectral_imaging.htm and CytovivaHyperspectral Imaging System Manual)

Acquisition of Spectral Scans from Hyperspectral Image

The CytoViva Hyperspectral image analysis software powered by ENVIcontains important features to aid in the quantification andidentification of materials by spectral data analysis. At the beginningof each hyperspectral image analysis, images were corrected for darkcurrent values obtained after blocking illumination.

In this system, radiation emanating from cells illuminated with halogenlamp is collected on the objective lens, in turn translating into animage on the entrance-slit plane, which is in turn projected onto theprism-grating-prism components. Consequently, the radiation changes itsdirection of propagation depending on the wavelength. Each area of thecells is represented as a set of monochromatic points on the detector,translating continually into a spectrum along the spectral axis.Movement of the objective lens amounts to variation in the regioncaptured along with variation the wavelength captured. A set of suchimages captured at varying camera locations thus yielded all regions andwavelengths of the sample. In these experiments, a total of 3 imageswere recorded per sample and were analyzed pixel-wise utilizing theRegions of Interest (ROI)® tool. At least ten groups of pixels wereanalyzed per image. Spectral data was then extracted from each selectedROI and the mean of means of each ROI was calculated based on thefollowing equation:Mean R(λ)=[float(S1)+(S2)+(S3)+(Sn)]/number of ROIs

Irregularities stemming from non-uniformity of the spectral source andinfluence of the dark current are accounted for through normalization ofthe image data. This normalization was performed by considering thehighest intensity of a sample in the entire wavelength range i.e.400-1000 nm as “1” and then calculating the normalized intensity foreach wavelength according to the following equation:R(λ)=float(S1)/max(S1)

Each point in the cytoplasm of cells has a sequence of relativetransmittance in the entire wavelength range of the spectrum that makesthe spectral diagram or spectral signature of a point. In theexperiments described herein, the spectral diagrams for cells exposed todesired experimental condition were evaluated to extract the differencesbetween β-amyloid peptide treated and untreated cells in the presence orabsence of β-amyloid aggregation promoters or inhibitors. (Siddiqi etal., Cancer. 2008; 114(1):13-21; Khoobehi et al., Invest Ophthalmol VisSci. 2004; 45(5):1464-72)

Spectral Angle Mapping Classification Algorithm

Among supervised classification methods, a SAM classification algorithmwas selected due to its better performance than other classificationalgorithms for detection of β-amyloid aggregates in unknown samples. TheSAM algorithm is a tool for rapid mapping of the spectral similarity ofimage spectra to reference spectra. The SAM is a physically basedspectral classification that uses an n-dimensional angle to match pixelsto reference spectra. This method determines the spectral similarity bycalculating the angle between the spectra, treating them as vectors in aspace with dimensionality equal to the number of bands or wavelengths.The angle between the endmember spectrum vector and each pixel vector inn-dimensional space is then compared. Smaller angles represent closermatch to a reference spectrum. Pixels further away from the specifiedmaximum angle threshold in radians are not classified. In this study,the reference spectra were extracted from region of interest (ROI) inthe cytoplasm of cells treated with Aβ₁₋₄₂ peptide. For the SAMclassification, the spectral library of Aβ₁₋₄₂ aggregates was created byscanning a stock solution of Aβ₁₋₄₂ peptide which was allowed tooligomerize in vitro and saved in advance. The spectral angle parametervalue as α=0·1 or 0·2 was used for a SAM classifier where a is definedas the angle between testing spectrum vector α, and reference spectrumvector b and is calculated using the following equation. (Park et al.,Biosys Eng. 2007, 96 (3):323-33)) (Also, see FIG. 14 and Siddiqi et al.,Cancer, 114(1), 13-21 (2008).

$\alpha = {\cos^{- 1}\left( \frac{\overset{\rightarrow}{a} \cdot \overset{\rightarrow}{b}}{{\overset{\rightarrow}{a}} \cdot {\overset{\rightarrow}{b}}} \right)}$

Hyperspectral Analysis of Mouse Brain and Retina

Brain and retina tissue were isolated from transgenic Alzheimer's andage-matched wild type mice at 2, 4, 6, 8 and 10 months of age.

-   -   (a) Isolation and analysis of brain tissue. Brains were removed        from wild type and Alzheimer's mice and post fixed in Zamboni's        fixative (4% paraformaldehyde and 15% picric acid in 0.25 M        sodium phosphate, pH 7.5) for 48 h before being cryopreserved in        a 30% (wt/vol) sucrose/0.1 sodium phosphate-buffered saline        solution. Frozen sections (10 μm) in OCT were cut on a sliding        microtome, brought to room temperature and were coverslipped        with hardset Vectashield mounting medium with the nuclear stain        DAPI (catalogue #H-1500; Vector Laboratories, Burlingame, CA).        The whole-mount brain slides were scanned with Cytoviva        microscope and spectral signatures were collected from        wavelengths in the 400-1000 nm range as described before.    -   (b) Isolation and analysis of retina tissue. Eyes were        enucleated from wild type and Alzheimer's mice at the desired        age. For whole-mount retinas, eyes were fixed in ˜2 mL of        freshly prepared 4% PFA-PBS at room temperature for 45 minutes.        This was followed by washing with ice-cold PBS solution (2 mL)        at least five times. The anterior eye portion, cornea, was        dissected out under surgical microscope. The iris was then        removed followed by the sclera, lens and hyaloid vessels. The        isolated retinas were then washed with ice-cold PBS and divided        into four quadrants by making four radial incisions. The        whole-mounts were prepared by transferring the dissected retinas        onto a microscope slide and coverslipped with hardset        Vectashield mounting medium with the nuclear stain DAPI. The        whole-mount retina slides were scanned with Cytoviva microscope        and spectral signatures were collected from wavelengths in the        400-1000 nm range as described before.    -   (c) Immunohistochemistry of mouse brain and retina samples. For        immunofluorescence studies, brain section slides and retina        sample slides were pre-incubated for 1 hour in 5% normal goat        serum (NGS) in 1×PBST (1× PBS containing 0.3% Triton X-100) at        room temperature. A primary antibody against β-amyloid peptide        ((Cell signaling, Cat. #2454) was employed then at a dilution of        1:200 in 1% NGS in 1×PBST. After an overnight incubation at 4°        C., the slides were rinsed thrice for 10 min with 1×PBST and        then incubated for 2 h in goat anti-rabbit IgG conjugated to Cy3        diluted to 1:1000 in 1% NGS in 1×PBST. The sections were rinsed        in PBST thrice for 10 min and in PBS for 5 min. Samples were        then dehydrated in ethanol, cleared with methyl salicylate,        mounted in DEPEX (Electron Microscopy Science, Poole, UK) and        staining of β-amyloid aggregates and plaques was visualized with        Cytoviva microscope.

Statistical Analysis of Data

The spectral data were analyzed to detect differences between cellstreated with or without β-amyloid peptide in the presence or absence ofinhibitors. The differences between the mean transmittance at eachwavelength for samples under various treatments were compared by theunpaired Student's t test (two-tailed test) or by the multivariateanalysis of variance (ANOVA), as appropriate. Values for each wavelengthwere reported as means ± SD. A p value of 0.05 was consideredsignificant. Similarly, for tissue samples, spectral differences betweenAlzheimer's and wild type mouse tissue at a particular time point wereanalyzed by the unpaired Student's t test with p<0.05 considered to besignificant.

Reagents

Aβ₁₋₄₂, FITC-Aβ₁₋₄₂ and FITC-scrambled-Aβ₁₋₄₂ were purchased fromAmerican Peptide Company (Sunnyvale, CA, USA). All other chemicals werepurchased from Sigma (St. Louis, MO, USA). For all experiments, Aβ₁₋₄₂was dissolved in 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) to aconcentration of 1 mg/mL, sonicated in a water bath for 10 min and driedunder vacuum. The HFIP-treated Aβ₁₋₄₂ was dissolved in dimethylsulfoxide(DMSO) to a final concentration of 1 mM and stored at −20° C. Stocksolutions of FITC-Aβ₁₋₄₂ and FITC-scrambled-Aβ₁₋₄₂ were prepared in asimilar manner. The cell culture media MEM, F12, and fetal bovine serum(FBS) were obtained from Invitrogen (Carlsbad, CA).

Cell Culture and Cellular Uptake.

The human neuroblastoma cell line, SH-SY-5Y, used in the present studieswas obtained from American Type Culture Collection (Manassas, VA). Thecells were maintained in MEM:F12 (1:1) medium supplemented with 10% FBS,100 units/mL penicillin and 100 units/mL streptomycin and 1% NEAA(non-essential amino acid). Cells were grown at 37° C. in a humidifiedatmosphere with 5% CO2/95% air. FITC-Aβ₁₋₄₂, and FITC-scrambled-Aβ₁₋₄₂,were added to SHSY5Y cultures for 24 h. For time-dependence experiments,250 nM FITC-Aβ₁₋₄₂ was added to SHSY5Y cells, plated in 4-well Lab-Tekchamber slides (Nunc) and images as well as spectral scans (Cytoviva)were acquired at varying times (0-5 days) after addition of thelabeled-Aβ₁₋₄₂. For dose-dependence experiments, FITC-Aβ₁₋₄₂ was addedat varying concentrations (0-1000 nM) and imaged 24 h thereafter. Insome experiments, SH-SY-5Y cells were incubated with FITC-Aβ₁₋₄₂ for 48h in the presence and absence of inhibitors or promoters of β-amyloidpeptide.

Animals

Female APP and PS1 double transgenic mice (6-8 weeks old, catalogue#005864) and wild type C57BL6 mice were purchased from JacksonLaboratories (Bar Harbor, ME) and housed in SPF conditions, whichincluded filtered air, sterilized food, water, bedding, and cages, for 2weeks before use. All experiments were approved by the InstitutionalAnimal Care and Use Committee at the University of Minnesota. Allexperimental and animal handling procedures were in accordance withnational ethical guidelines. Mice were maintained on standard food andwater ad libitum.

Example 2 Early Detection of Alzheimer's Disease in Humans

Hyperspectral imaging technology can be used for early detection ofAlzheimer's disease in humans. To this end, the current Cytoviva®instrument will be modified to enable it to apply light through theretina of the patient and collect the emitted light in such a mannerthat it can be passed through a Cytoviva spectrophotometer to recordspectral data.

The spectral data can in turn be analyzed, e.g., in three ways:

-   -   1) As part of an annual exam, a patient may obtain a spectral        signature at a particular age and this spectral information will        be compared during annual exams in successive years. A        significant difference compared to the normal deviation that        would occur with age would be considered worthy of further        specific evaluation for neurodegenerative disorders.    -   2) A group of normal and Alzheimer's individuals will be imaged        to build a reference spectral library for a particular age        range. The spectral data of an unknown individual would be        compared to this reference library and its similarity with the        two aforementioned groups will be evaluated.    -   3) Once the person is recognized, either genetically or        otherwise through one of the above two novel methods to be        susceptible to Alzheimer's disease, treatment may be initiated,        with the degree of success of the treatment being tied to        deviations from the patient's pre-treatment spectral signature        toward the normal group.

In each of the cases, either the entire spectrum in the wavelength rangeof about 400-1000 nm or only a few selected wavelength ranges can beused for comparison purpose.

Example 3 High Throughput Screening

High throughput screening can be performed in cell culture models asdescribed in Example 2. The changes in hyperspectral scans after thetreatment will be compared with the normal and diseased groups.Similarly, the success of AD treatment in humans will be analyzed asdescribed herein.

Example 4 Hyperspectral Imaging: A Tool for Screening of InhibitorsAgainst β-Amyloid Aggregation

Protein folding constitutes progressive conformational definition of arandom coiled polypeptide chain first into finite secondary structuresand then into tertiary or quaternary structures that confer functionalcapability upon the protein. Although regulated strictly bytranslational order and redox environmental controls, protein folding isnot infallible. While a majority of misfolded proteins undergoproteolysis and/or phagocytosis, some resist these so-called “qualitycontrol” checks. A small subset of such resistant proteins are toxic ontheir own accord, and a yet smaller subset are conformational nucleatorsthat induce misfolding in other polypeptide chains. The latter may beexo- or endogenous. Exogenous protein misfolding nucleators arepopularly known as prions and prion-induced disease is subject topreventive measures similar to those against DNA-bearing infectiousagents. Endogenous protein misfolding nucleators are far more insidious,their origin usually being the misfolding of a normal physiologicalprotein or a polypeptide that is often produced in large quantities.Alzheimer's Disease (AD) molecular pathology showcases a consequence ofthe misfolding of the amyloid-β (Aβ) peptide fragments (Aβ¹⁻⁴⁰, Aβ¹⁻⁴²),that are produced during proteolysis of the membrane associated amyloidprecursor protein. The Aβ peptide fragments are amenable to misfoldinginto β-pleated sheet structures that in turn are nucleators of theβ-sheet secondary structure. Higher ordered Aβ sheets are termedfibrils, whose solubility decreases with order. Dense, highly ordered Aβclumps are the dreaded “plaques” apparent in the post-mortem autopsy ofindividuals with end-stage AD. Whether Aβ deposition induces cognitivedecline or vice-versa is a rather energetically debated matter withinthe area, nevertheless, there exists agreement that appearance of Aβplaques is an indicator of AD. Cognitive decline in AD patients was notcorrelated with the levels of senile plaque formation or insoluble Aβformation; instead it correlated with the levels of synapse loss and thelevels of soluble Aβ. These soluble toxic forms of Aβ in AD brains haverecently been identified to be oligomeric assemblies of Aβ. Thus,amyloid aggregation is thence an attractive therapeutic target forintervention with small molecules.

Amyloidopathy is believed to occur very early in AD development. Earlycognitive decline associated with AD (eAD) may be the first clinicallytractable pathology, but amyloidopathy is already established firmly atthis point. Early intervention into amyloidopathy with small moleculeswould be fruitful in theory, however, the lack of suitable diagnostictools for both—the rapid screening of small molecule Aβ aggregationinhibitors and for early detection of AD pathology complicate the drugdevelopment and drug administration aspects of AD management. Extantmolecular screens for misfolded Aβ are cell-free and consist of dyes(e.g., thioflavin-T, congo red) whose binding to Aβ fibrils causescharacteristic spectral change, which is unfortunately subject tovariance in the presence of small molecules as would be the case duringan inhibitor screen. Mass-spectrometry based screen may be able toidentify Aβ fibrillogenesis inhibitors but not those of Aβoligomerization. Cell-culture and cytotoxicity models thus still remainthe mainstay of Aβ aggregation inhibitor screening. All of the existingmodels of this type employ altered forms of Aβ (such as a GFP-Aβ hybrid)that would aid detection or require unrealistically high concentrationsof the expensive Aβ peptide.

Described herein is the development of a detection technique for Aβaggregation based on the principle of hyperspectral imaging (HSI). ACytoviva® instrument captures the visible near-IR (400-1000 nm) spectrumwithin each pixel of the microscopic view field. The informationobtained is a spatial distribution of light transmittance with apurportedly high signal-to-noise ratio. In essence, such a high spectralresolution is expected to discern between pixels that representcytoplasm with varying amounts of unlabelled, native insoluble Aβ, and awide wavelength range spectral scan beyond the visible range would beexpected to highlight characteristic light-transmittance properties ofvarious cytoplasmic components. Described herein are studies examiningwhether hyperspectral imaging of cytoplasm highlights any characteristictrends that correlate with Aβ accumulation; whether the trend identifiedis unique to Aβ aggregation, thus paving way for definition of a Aβaccumulation “signature” and hence the foundation of a diagnostic tool,and whether the presence of Aβ aggregation inhibitors is compatible withthe collection of hyperspectral images so as to form the basis for apotential high-throughput screen with greatly increased facility andsensitivity when compared to conventional methods.

Results and Discussion.

HSI spectral signature of Aβ¹⁻⁴² aggregation. The uptake of Aβ¹⁻⁴² wasverified through incubation of SH-SY5Y cells with 0-1000 nMconcentrations of Aβ¹⁻⁴² followed by measurement of intracellularfluorescence. It was demonstrated that cytoplasmic fluorescenceintensity rises in proportion to the concentration of Aβ¹⁻⁴² to whichthe cells are exposed. Organelle distribution of the peptide was notcharacterized in this experiment, but others have discussed traffickingof Aβ¹⁻⁴² into late lysosomes and vesicles derived therefrom. HSIspectra collected also reveal changes in the 400-1000 nM wavelengthregion, where transmitted light shifts to lower values, the magnitude ofthis shift being proportional to the concentration of Aβ¹⁻⁴². The changein light absorbance between the 400-1000 nM wavelength range in the HSIspectra of cells exposed to Aβ¹⁻⁴² appears to be highly specific for theaggregated form of the peptide, as the sequence-scrambled form ofAβ¹⁻⁴², although accumulating to an equal extent inside the cell, doesnot produce the characteristic HSI shift.

Temporal changes in HSI spectra of cells upon exposure to Aβ¹⁻⁴² weremeasured by exposure of cells to 250 nM Aβ¹⁻⁴² followed by collection ofHSI spectra over time. Transmitted light reduced gradually in the periodfollowing 24 h of incubation, reaching its nadir at 48 h. Unexpectedlythe period leading up to the 72 h time-point was characterized bygradual regain of light transmittance tending toward values of cells nottreated with Aβ¹⁻⁴² or those treated with sequence-scrambled Aβ¹⁻⁴².This trend continued even after week long incubation with the peptide.Macromolecular changes in intracellular amyloid protein content andaggregation and the effects of the changes on spectral characteristicsas cells are exposed to beta-amyloid were also determined. Early stagesconsist of diffusion of amyloid into the cell toward equilibrium withthe extracellular space. Continued amyloid accumulation inside the cellresults in aggregation. At time=24 h, soluble amyloid fibrils are thedominant amyloid formations and their presence does not alter spectralsignature. The period between 24 and 36 h is characterized by amyloidaggregation increasing in order and producing progressively insolubleaggregates that block light and therefore alter spectral signature.Insoluble amyloid aggregates nucleate further ordering of amyloidaggregates into insoluble species resulting in a diffuse mesh ofinsoluble aggregates at time=48 h. The spectral signature at this timeperiod is correspondingly the most altered when compared to time=0 h.Beyond 48 h, the diffuse mesh of insoluble aggregates begins to coalesceinto dense plaques. Although harboring more amyloid content than thediffuse aggregates, the plaques block lesser surface area and theamyloid induced change in spectral signature is apparently reduced.

Utility of the HSI spectral signature in inhibitor screening. Havingidentified a unique HSI signature for cellular Aβ¹⁻⁴² aggregation, theutility of this finding for screening of inhibitors was investigated.Guanidine, guanosine and urea are known to interfere in amyloidaggregation through sequestration of electrophilic species that formamyloidogenic advanced glycation end-products (AGEs) with proteins.Cells co-incubated with these inhibitors showed attenuation ofamyloid-induced HSI spectral change, with some reaching that of cellsnot treated with Aβ¹⁻⁴². The magnitude of signature-attenuationcorresponded to the reported potency of the test inhibitor; thus,guanidine was found to afford the greatest attenuation in HSI spectralchange followed sequentially by guanosine and urea—in parallel to theirreported potencies of inhibiting amyloid formation inhibition.

HSI spectral signatures in amyloid aggregate mapping and quantitation.The Spectral Angle Mapper (SAM) technique, as described herein, allowsobtainment of the spectral signature of a single object—in this case theobject being an Aβ¹⁻⁴² aggregate. Utilization of FITC-labelled Aβ¹⁻⁴²enabled visual localization of intracellular aggregates. HSI scanning ofthe visually located aggregate afforded a specific spectral signature ofthe aggregate. This process, when repeated across several aggregatesrevealed that SAM-collected signature of all Aβ¹⁻⁴² aggregates issimilar and thus appears to be a unique characteristic. Such a signaturecan be used for mapping of Aβ aggregates throughout the cytoplasm of anunknown sample. Through this process, the density and the localizationof Aβ aggregates could be studied. As a test case, cells were exposed toa known amyloid aggregation inhibitor (guanidine) and a known amyloidaggregation promoter (Zn²⁺). The number of intracellular amyloidaggregates were lowered to 62% in case of cells treated with guanidinewhen compared to cells treated with Aβ¹⁻⁴² alone. This number changes to280% in case of Zn²⁺ treated cells. HSI imaging coupled with SAM is thusable to differentiate between amyloid aggregation promoters andinhibitors. This ability to classify compounds according to theiramyloidogenic potential will be of interest for drug discovery andtoxicology investigations.

Utility of HSI techniques for in-vivo monitoring of amyloidogenesis. HSIspectral signatures from brain samples from patients identifiedclinically as Alzheimer's inflicted varied from those from age-matchednormal individuals. The type of spectral variation was similar to thecharacteristic difference observed between normal cells and Aβ¹⁻⁴²treated cells. Total transmittance in the samples from Alzheimer'spatients was lower, reflecting dispersion of amyloid aggregates andaccompanying morphological and biochemical changes. A similar experimentin retinal tissue samples from normal and Alzheimer's afflicted humansoffered similar results.

The retina is considered diagnostically an extension of the CNS and canbe accessed with non-invasive methods. The reproducible and tangibledifferences observed in retinal samples in the present experimentsprompted led to the consideration of whether these changes could be usedas a potential mode of AD diagnosis.

The retinae of transgenic APP/PS1 mice were imaged with the HSItechnique. HSI scans of mice were acquired at 2, 4, 6 and 8 months ofage. Differences between normal and APP/PS1 mice began to appear at 4months of age, and statistically significant differences were observedat the age of 6 months onward. At the age of 6 months, frank amyloidaggregates were not detected in retinal tissue. At the same age,aggregates had begun to appear in the brains of these mice. At the ageof 8 months, the HSI spectral difference was prominent and aggregateswere clearly observable in brain tissue, but barely visible in theretina. As such, the HSI spectral difference in the retina isindependent of the appearance of frank amyloid plaque deposition. Sinceclinical effects of amyloid plaque deposition appear well afteramyloidogenesis has set in, detection of amyloid HSI signature in theretina is an early diagnostic tool for amyloidopathy.

The utility of the HSI imaging diagnostic method in monitoring thedevelopment of Alzheimer's disease in a treatment program was evaluatedwith an experimental anti-Alzheimer's drug candidate, ψ-GSH. (More etal., ACS Chem. Neurosci. 2012, DOI: 10.1021/cn3001679). Transgenic(APP/PS1) and wild type were treated i.p. with ψ-GSH for 12 weeks,beginning at the age of 3 months. Every four weeks, retinae wereisolated and HSI spectra were acquired. Retinae at 4 months, i.e., onemonth after initiation of treatment, showed no statistically significantdifference, reciprocating earlier experiments. HSI spectra began todiffer between the normal and Alzheimer's mice after 2 months oftreatment. The spectra from the retinae of mice treated with W-GSHtended toward those from normal mice. This difference persistedthroughout the treatment and 3 months thereafter. Mice treated orallywith W-GSH did not exhibit any differences from those of transgenicmice, mirroring the behavioral effects observed in this experiment.These findings were confirmed with the memory test in Morris Water mazeand immunohistochemistry on the brain tissue. Mice treated i.p. withψ-GSH showed significant learned behavior inculcation during the firstweek of testing, while untreated transgenic mice did not. Escapelatencies for mice treated with ψ-GSH (day 3: 17.91±4.65 s; day 4:14.64±2.61 s) were similar to those for WT saline-treated mice (day 3:17.29±2.13 s; day 4: 12.42±2.18 s). The escape latency values for thei.p. ψ-GSH treated APP-PS1 mice and those for saline-treated APP-PS1mice were also significantly different (one-way ANOVA, p<0.001). Pathlengths traversed by the ψ-GSH treated APP-PS1 mice correlated well withcorresponding escape latencies. In fact, ψ-GSH treated APP-PS1 micetraversed paths of lengths similar to saline-treated WT mice. In theprobe trial, APP-PS1 mice spent only 16.39±3.39% of the time in thetarget quadrant, while the APP-PS1 (i.p. ψ-GSH) and non-transgenicvehicle controls retained significantly greater memory, spending 38.43 t3.73% and 36.67±5.30%, respectively, in the target quadrant. Braintissue sections of i.p. ψ-GSH treated APP/PS1 mice had significantlylower Aβ load than the corresponding untreated mice. The number andsizes of Aβ plaques were drastically reduced in the ψ-GSH treated group.In APP/PS1 mice treated orally with ψ-GSH, trends toward higher spatialmemory development and lower escape latencies were noted relative to thesaline-treated group, but did not reach statistical significance. In theprobe trial, orally treated APP/PS1 mice spent 21.76±5.36% in the targetquadrant; similar to saline treated transgenic controls. Brains oforally treated APP/PS1 mice showed a modest decrease in Aβ plaquesrelative to controls. Results of biochemical and behavioral studies werein agreement with the hyperspectral data. This provides a basis forutilization of hyperspectral imaging to determine the progress oftreatment. This will help avoid lengthy experimentation time and improvethe ability to test more compounds.

Materials and Methods

Reagents Aβ₁₋₄₂, FITC-Aβ₁₋₄₂ and FITC-scrambled-Aβ₁₋₄₂ were purchasedfrom American Peptide Company (Sunnyvale, CA, USA). All other chemicalswere purchased from Sigma (St. Louis, MO, USA). For all experiments,Aβ₁₋₄₂ was dissolved in 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) to aconcentration of 1 mg/mL, sonicated in a water bath for 10 min and driedunder vacuum. The HFIP-treated Aβ₁₋₄₂ was dissolved in dimethylsulfoxide(DMSO) to a final concentration of 1 mM and stored at −20° C. Stocksolutions of FITC-Aβ₁₋₄₂ and FITC-scrambled-Aβ₁₋₄₂ were prepared in asimilar manner. The cell culture media MEM, F12, and fetal bovine serum(FBS) were obtained from Invitrogen (Carlsbad, CA).

Cell Culture and Cellular Uptake. The human neuroblastoma cell line,SH-SY-5Y, used in the present study was obtained from American TypeCulture Collection (Manassas, VA). The cells were maintained in MEM:F12(1:1) medium supplemented with 10% FBS, 100 units/mL penicillin and 100units/mL streptomycin and 1% NEAA (non-essential amino acid). Cells weregrown at 37° C. in a humidified atmosphere with 5% C02/95% air.FITC-Aβ₁₋₄₂, and FITC-scrambled-Aβ₁₋₄₂, were added to SHSY5Y culturesfor 24 h. For time-dependence experiments, 250 nM FITC-Aβ₁₋₄₂ was addedto SHSY5Y cells, plated in 4-well Lab-Tek chamber slides (Nunc) andimages as well as spectral scans (Cytoviva) were acquired at varyingtimes (0-5 days) after addition of the labeled-Aβ₁₋₄₂. Fordose-dependence experiments, FITC-Aβ₁₋₄₂ was added at varyingconcentrations (0-1000 nM) and imaged 24 h thereafter. In someexperiments, SH-SY-5Y cells were incubated with FITC-Aβ₁₋₄₂ for 48 h inthe presence and absence of inhibitors or promoters of β-amyloidpeptide.

CytoViva hyperspectral imaging System After each treatment, slides wereexamined utilizing a CytoViva microscope and hyperspectral imagingsystem (CytoViva-Hyperspectral Imaging System (HSI), Auburn, AL; see theCytoviva Hyperspectral Imaging System Manual) mounted on an OlympusBX-41 optical microscope. This system employs a darkfield-basedilluminator that focuses a highly collimated light at oblique angles onthe sample to obtain images with improved contrast and signal-to-noiseratio. Assembly of diffraction grating system in an imagingspectrophotometer with 1.29 nm spectral resolution (12.5 μm slit) wasused. Utilization of this concept obviated the necessity of extraneousagents (e.g., staining or contrast agents), as the core imagingtechnique relies on light scattering/transmittance and resolution ofscattered/transmitted light in the visible and near-IR wavelengths.Light scattering is a property unique to every type of insolubleparticulate matter, ergo, spectral information relayed by this techniquecorrelates directly to the location and type (or size) of particulatematter in question. In this experiment, the ENvironment forVisualization (ENVI ver. 4.4) software was employed to control theresolution of scattered light and aggregation of β-amyloid peptide wasthe subject of interest.

The images were captured at 40× magnification using ENVI software, whichis followed by extraction of spectral curves as described in the nextsection. The camera captured spectral responses from 400-1000 nm with amaximum readout time of 12 frames per second. To aid in theidentification of Aβ₁₋₄₂ aggregates in unknown samples, a spectrallibrary of Aβ₁₋₄₂ aggregates was created using FITC-labeled Aβ₁₋₄₂ inthe cell culture experiments. After establishment of this referencelibrary, the spectral angle mapping algorithm was employed forcomparison of the distinct spectral features of the library with thespectral scan of the unknown sample (described in Spectral Angle MappingClassification Algorithm).

Acquisition of Spectral Scans from Hyperspectral Image The CytoVivaHyperspectral image analysis software powered by ENVI contains featuresto aid in the quantification and identification of materials by spectraldata analysis. At the beginning of each hyperspectral image analysis,images were corrected for dark current values obtained after blockingillumination.

In this system, radiation emanating from cells illuminated with halogenlamp is collected on the objective lens, in turn translating into animage on the entrance-slit plane, which is in turn projected onto theprism-grating-prism components. Consequently, the radiation changes itsdirection of propagation depending on the wavelength. Each area of thecells is represented as a set of monochromatic points on the detector,translating continually into a spectrum along the spectral axis.Movement of the objective lens amounts to variation in the regioncaptured along with variation the wavelength captured. A set of suchimages captured at varying camera locations thus yielded all regions andwavelengths of the sample. In these experiments, a total of 3 imageswere recorded per sample and were analyzed pixel-wise utilizing theRegions of Interest (ROI)® tool. At least ten groups of pixels wereanalyzed per image. Spectral data was then extracted from each selectedROI and the mean of means of each ROI was calculated based on thefollowing equation:Mean R(λ)=[float(S1)+S2+S3+ . . . +Sn]/number of ROIsIrregularities stemming from non-uniformity of the spectral source andinfluence of the dark current are accounted for through normalization ofthe image data. This normalization was performed by considering thehighest intensity of a sample in the entire wavelength range i.e.400-1000 nm as “1” and then calculating the normalized intensity foreach wavelength according to the following equation:R(λ)=float(S1)/max(S1)Each point in the cytoplasm of cells has a sequence of relativetransmittance in the entire wavelength range of the spectrum that makesthe spectral diagram or spectral signature of a point. In theseexperiments, the spectral diagrams for cells exposed to desiredexperimental condition were evaluated to extract the differences betweenβ-amyloid peptide treated and untreated cells in the presence or absenceof β-amyloid aggregation promoters or inhibitors. (also, see Siddiqi, etal., (2008) Use of hyperspectral imaging to distinguish normal,precancerous, and cancerous cells. Cancer, 114, 13-21 and Khoobehi etal., (2004) Hyperspectral imaging for measurement of oxygen saturationin the optic nerve head. Invest Ophthalmol Vis Sci., 45, 1464-72.)

Spectral Angle Mapping Classification Algorithm Among supervisedclassification methods, a SAM classification algorithm was selected dueto its better performance than other classification algorithms fordetection of p-amyloid aggregates in unknown samples. (Park et al.,Contaminant Classification of Poultry Hyperspectral Imagery using aSpectral Angle Mapper Algorithm. Biosys Eng., 96, 323-333) The SAMalgorithm is a tool for rapid mapping of the spectral similarity ofimage spectra to reference spectra. The SAM is a physically basedspectral classification that uses an n-dimensional angle to match pixelsto reference spectra. This method determines the spectral similarity bycalculating the angle between the spectra, treating them as vectors in aspace with dimensionality equal to the number of bands or wavelengths.The angle between the endmember spectrum vector and each pixel vector inn-dimensional space is then compared. Smaller angles represent closermatch to a reference spectrum. Pixels further away from the specifiedmaximum angle threshold in radians are not classified. In this study,the reference spectra were extracted from region of interest (ROI) inthe cytoplasm of cells treated with Aβ₁₋₄₂ peptide. For the SAMclassification, the spectral library of Aβ₁₋₄₂ aggregates was created byscanning a stock solution of Aβ₁₋₄₂ peptide which was allowed tooligomerize in vitro and saved in advance. The spectral angle parametervalue as α=0·1 or 0·2 was used for a SAM classifier where a is definedas the angle between testing spectrum vector a, and reference spectrumvector b and is calculated using the following equation: (Also, see FIG.14 , and Siddiqi et al., Cancer, 114(1), 13-21 (2008).

$\alpha = {\cos^{- 1}\left( \frac{\overset{\rightarrow}{a} \cdot \overset{\rightarrow}{b}}{{\overset{\rightarrow}{a}} \cdot {\overset{\rightarrow}{b}}} \right)}$

Animals Female APP and PS1 double transgenic mice (6-8 weeks old,catalogue #005864) and wild type C57BL6 mice were purchased from JacksonLaboratories (Bar Harbor, ME) and housed in SPF conditions, whichincluded filtered air, sterilized food, water, bedding, and cages, for 2weeks before use. All experiments were approved by the InstitutionalAnimal Care and Use Committee at the University of Minnesota. Allexperimental and animal handling procedures were in accordance withnational ethical guidelines. Mice were maintained on standard food andwater ad libitum.

Hyeprspectral and Immunohistochemical Analysis of Mouse Brain and RetinaBrain and retina tissue were isolated from transgenic Alzheimer's andage-matched wild type mice at 2, 4, 6, and 8 months of age.

-   -   (a) Isolation and analysis of brain tissue. Brains were removed        from wild type and Alzheimer's mice and post fixed in Zamboni's        fixative (4% paraformaldehyde and 15% picric acid in 0.25 M        sodium phosphate, pH 7.5) for 48 h before being cryopreserved in        a 30% (wt/vol) sucrose/0.1 sodium phosphate-buffered saline        solution. Frozen sections (10 μm) in OCT were cut on a sliding        microtome, brought to room temperature and were coverslipped        with hardset Vectashield mounting medium with the nuclear stain        DAPI (catalogue #H-1500; Vector Laboratories, Burlingame, CA).        The whole-mount brain slides were scanned with Cytoviva        microscope and spectral signatures were collected from        wavelengths in the 400-1000 nm range as described.    -   (b) Isolation and analysis of retina tissue. Eyes were        enucleated from wild type and Alzheimer's mice at the desired        age. For whole-mount retinas, eyes were fixed in ˜2 mL of        freshly prepared 4% PFA-PBS at room temperature for 45 minutes.        This was followed by washing with ice-cold PBS solution (2 mL)        at least five times. The anterior eye portion, cornea, was        dissected out under surgical microscope. The iris was then        removed followed by the sclera, lens and hyaloid vessels. The        isolated retinas were then washed with ice-cold PBS and divided        into four quadrants by making four radial incisions. The        whole-mounts were prepared by transferring the dissected retinas        onto a microscope slide and coverslipped with hardset        Vectashield mounting medium with the nuclear stain DAPI. The        whole-mount retina slides were scanned with Cytoviva microscope        and spectral signatures were collected from wavelengths in the        400-1000 nm range as described before.    -   (c) Immunohistochemistry of mouse brain and retina samples. For        immunofluorescence studies, brain section slides and retina        sample slides were pre-incubated for 1 hour in 5% normal goat        serum (NGS) in 1× PBST (1× PBS containing 0.3% Triton X-100) at        room temperature. A primary antibody against β-amyloid peptide        ((Cell signaling, Cat. #2454) was employed then at a dilution of        1:200 in 1% NGS in 1×PBST. After an overnight incubation at 4°        C., the slides were rinsed thrice for 10 min with 1×PBST and        then incubated for 2 h in goat anti-rabbit IgG conjugated to Cy3        diluted to 1:1000 in 1% NGS in 1×PBST. The sections were rinsed        in PBST thrice for 10 min and in PBS for 5 min. Samples were        then dehydrated in ethanol, cleared with methyl salicylate,        mounted in DEPEX (Electron Microscopy Science, Poole, UK) and        staining of β-amyloid aggregates and plaques was visualized with        Cytoviva microscope.

Hyperspectral Imaging to follow treatment success in Alzheimer's miceAlzheimer's and wild type mice were treated with a candidate drug,ψ-GSH, three times a week for 12 weeks starting at the age of three tofour months. (see More et al., (2012) Restoration of Glyoxalase EnzymeActivity Precludes Cognitive Dysfunction in a Mouse Model of Alzheimer'sDisease. ACS Chem. Neurosci., DOI: 10.1021/cn3001679) The study wasdivided in four groups (10 mice/group). 1. APP/PS1 mice-vehicle control,2. APP/PS1 mice-ψ-GSH i.p. 500 mg/kg, 3. APP/PS1 mice-W-GSH oral 500mg/kg, 4. Non-transgenic wild type mice-vehicle control. One and twomonths after initiation of treatment and at the end of the study,animals were euthanized and retina tissues were isolated from animals ineach group followed by hyperspectral imaging as described under“Hyeprspectral Analysis of Mouse Brain and Retina”.

Statistical Analysis of data The spectral data were analyzed to detectdifferences between cells treated with or without β-amyloid peptide inthe presence or absence of inhibitors. The differences between the meantransmittance at each wavelength for samples under various treatmentswere compared by the unpaired Student's t test (two-tailed test) or bythe multivariate analysis of variance (ANOVA), as appropriate. Valuesfor each wavelength were reported as means ±SD. Aβ value of 0.05 wasconsidered significant. Similarly, for tissue samples, spectraldifferences between Alzheimer's and wild type mouse tissue at aparticular time point were analyzed by the unpaired Student's t testwith p<0.05 considered to be significant.

All documents cited herein are incorporated by reference. While certainembodiments of invention are described, and many details have been setforth for purposes of illustration, certain of the details can be variedwithout departing from the basic principles of the invention.

The use of the terms “a” and “an” and “the” and similar terms in thecontext of describing embodiments of invention are to be construed tocover both the singular and the plural, unless otherwise indicatedherein or clearly contradicted by context. The terms “comprising,”“having,” “including,” and “containing” are to be construed asopen-ended terms (i.e., meaning “including, but not limited to”) unlessotherwise noted. Recitation of ranges of values herein are merelyintended to serve as a shorthand method of referring individually toeach separate value falling within the range, unless otherwise indicatedherein, and each separate value is incorporated into the specificationas if it were individually recited herein. In addition to the orderdetailed herein, the methods described herein can be performed in anysuitable order unless otherwise indicated herein or otherwise clearlycontradicted by context. The use of any and all examples, or exemplarylanguage (e.g., “such as”) provided herein, is intended merely to betterilluminate embodiments of invention and does not necessarily impose alimitation on the scope of the invention unless otherwise specificallyrecited in the claims. No language in the specification should beconstrued as indicating that any non-claimed element is essential to thepractice of the invention.

What is claimed is:
 1. A system for spectral imaging, the systemcomprising: a light source for illuminating an eye tissue of a subjectover a range of wavelengths; one or more detectors for detecting lightreflected by the eye tissue; and a processor running a softwarecomprising instructions to: obtain spectral data of the eye tissue overthe range of wavelengths from the light detected by the one or moredetectors; and analyze the spectral data at multiple light bands overthe range of wavelengths to determine whether the spectral data isindicative of at least one of amyloidopathy or amyloidosis in thesubject.
 2. The system of claim 1, wherein the software is configured todetermine whether the spectral data is indicative of a formation ofβ-amyloid aggregates.
 3. The system of claim 2, wherein the β-amyloidaggregates comprise soluble β-amyloid aggregates.
 4. The system of claim2, wherein the β-amyloid aggregates are formed in one or more of abrain, eye, or central nervous system of the subject.
 5. The system ofclaim 1, wherein the range of wavelengths used to obtain the spectraldata are in a visible near infrared (VNIR) range.
 6. The system of claim1, wherein the spectral data is hyperspectral data.
 7. The system ofclaim 1, wherein the spectral data is obtained from a hyperspectralimage of the eye tissue over the range of wavelengths.
 8. The system ofclaim 1, wherein the software further comprises instructions to comparethe spectral data of the eye tissue to at least a first previousspectral data obtained from the eye tissue of the subject at an earlierpoint in time, wherein significant spectral differences between thespectral data of the eye tissue and the first previous spectral dataobtained from the eye tissue indicates the subject has one or moredisorders resulting from at least one of amyloidopathy or amyloidosis oris predisposed for developing one or more disorders resulting from atleast one of amyloidopathy or amyloidosis.
 9. The system of claim 1,wherein the software further comprises instructions to compare thespectral data from the subject to a control spectral data and to adisorder reference spectral data to determine whether the spectral datacomprises spectral differences that are indicative of one or moredisorders resulting from at least one of amyloidopathy and oramyloidosis.
 10. The system of claim 1, wherein the software furthercomprises instructions to compare the spectral data of the eye tissue toat least a first previous spectral data obtained from the eye tissue ofthe subject at an earlier point in time, wherein a decrease in formationof soluble β-amyloid aggregates is indicative of an effective treatmentof one or more disorders resulting from at least one of amyloidopathy oramyloidosis.
 11. The system of claim 1, wherein the spectral data isobtained non-invasively and without administration of dyes for detectionof β-amyloid aggregation.
 12. The system of claim 1, wherein at leastone of amyloidopathy or amyloidosis is indicative of presence or onsetof one or more of Alzheimer's disease, cerebral amyloid angiopathy,familial amyloid polyneuropathy, Parkinsons' disease, Huntington'sdisease, prolactinoma or a transmissible spongiform encephalopathy. 13.The system of claim 1, wherein the light source is a halogen lightsource.
 14. The system of claim 1, further comprising an objective lensconfigured to collect light reflected by the eye tissue.
 15. The systemof claim 1, further comprising a dispersive element.
 16. The system ofclaim 15, wherein the dispersive element comprises a prism.
 17. A systemfor spectral imaging, the system comprising: a light source forilluminating an eye tissue of a subject over a range of wavelengths; oneor more detectors for detecting light reflected by the eye tissue; and aprocessor running a software comprising instructions to: obtain spectraldata of the eye tissue over the range of wavelengths from the lightdetected by the one or more detectors; and analyze the spectral data atmultiple light bands over the range of wavelengths to determine whetherthe spectral data is indicative of a formation of amyloid aggregates.18. The system of claim 17, wherein the range of wavelengths used toobtain the spectral data are in a visible near infrared (VNIR) range.19. The system of claim 17, wherein the spectral data is hyperspectraldata.
 20. The system of claim 17, wherein the spectral data is obtainedfrom a hyperspectral image of the eye tissue over the range ofwavelengths.
 21. The system of claim 17, wherein the amyloid aggregatesare indicative of a disorder or a predisposition associated with atleast one of amyloidopathy or amyloidosis in the subject, wherein thedisorder is cerebral amyloid angiopathy, familial amyloidpolyneuropathy, Alzheimer's disease, Parkinson's disease (PD),Huntington's disease, prolactinoma or a transmissible spongiformencephalopathy.
 22. The system of claim 21, wherein the software furthercomprises instructions to compare the spectral data of the eye tissue toat least a first previous spectral data obtained from the eye tissue ofthe subject at an earlier point in time, wherein significant spectraldifference between the spectral data of the eye tissue and the firstprevious spectral data obtained from the eye tissue indicates thesubject has PD or is predisposed for developing PD.
 23. The system ofclaim 21, wherein the software further comprises instructions to comparethe spectral data from the subject to a control spectral data and to aPD reference spectral data to determine whether the spectral datacomprises spectral differences that are indicative of PD.
 24. The systemof claim 21, wherein the software further comprises instructions tocompare the spectral data of the eye tissue to at least a first previousspectral data obtained from the eye tissue of the subject at an earlierpoint in time, wherein a decrease in information of soluble β-amyloidaggregates is indicative of an effective treatment of PD.
 25. A systemfor spectral imaging, the system comprising: a light source forilluminating a cell over a range of wavelengths; one or more detectorsfor detecting light reflected by the cell; and a processor running asoftware comprising instructions to: obtain spectral data of the cellover the range of wavelengths from the light detected by the one or moredetectors; and analyze the spectral data at multiple light bands overthe range of wavelengths to determine whether the spectral data isindicative of a progression of one or more disorders associated with atleast one of amyloidopathy or amyloidosis.
 26. The system of claim 25,wherein the one or more disorders comprise cerebral amyloid angiopathy,familial amyloid polyneuropathy, Alzheimer's disease, Parkinson'sdisease (PD), Huntington's disease, prolactinoma or a transmissiblespongiform encephalopathy.